Authors: Dette, Holger
Nagel, Eva-Renate
Neumeyer, Natalie
Title: A Note on Testing Symmetry of the Error Distribution in Linear Regression Models
Language (ISO): en
Abstract: In the classical linear regression model the problem of testing for symmetry of the error distribution is considered. The test statistic is a functional of the difference between the two empirical distribution functions of the estimated residuals and their counterparts with opposite signs. The weak convergence of the difference process to a Gaussian process is established. The covariance structure of this process depends heavily on the density of the error distribution, and for this reason the performance of a symmetric wild bootstrap procedure is discussed in asymptotic theory and by means of a simulation study.
Subject Headings: M-estimation
goodness-of-fit tests
testing for symmetry
empirical process of residuals
linear model
Issue Date: 2003
Provenance: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

Files in This Item:
File Description SizeFormat 
25_03.pdfDNB188.06 kBAdobe PDFView/Open
tr25-03.ps402.04 kBPostscriptView/Open

This item is protected by original copyright

Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.